Summary of the Committee to Advise on Tropical Medicine and Travel (CATMAT) Statement on Travelers’ Diarrhea
Bibliographic record
Abstract
BACKGROUND: . METHODS: Following a systematic review of the literature, recommendations on the prevention and treatment of TD were developed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology to evaluate data quality, benefits and harms of the intervention, and values and preferences of the traveller. Other recommendations were based on a review of the literature and expert opinion. RECOMMENDATIONS: Using the GRADE methodology, CATMAT concluded that oral cholera vaccine should not be routinely recommended to prevent TD in Canadian travellers. This recommendation was based on moderate quality data that showed this vaccine was not effective in preventing TD in travellers compared to placebo. Bismuth subsalicylate (BSS), fluoroquinolones or rifaximin are options for the prevention of TD based on high-quality data for BSS and fluoroquinolones and moderate evidence for rifaximin. For the treatment of TD, loperamide (alone or in combination with antibiotics), fluoroquinolones, azithromycin and rifaximin are all options, with varying degrees of data quality. Based on available evidence and expert opinion, CATMAT recommends handwashing or the use of hand sanitizer, as well as prudent choice and preparation of food and beverages as best practices for preventing diarrhea while travelling. At this time, a recommendation cannot be made for either the use of probiotics and prebiotics to prevent TD or the use of BSS to treat TD due to insufficient available evidence. CONCLUSION: With the exception of BSS for prevention of TD (strong recommendation for use), CATMAT conditionally recommends the use of each of the other GRADE-evaluated preventive and therapeutic products assessed in this Statement. These CATMAT recommendations should be considered as options in the prevention and treatment of TD based on the particular situation of the traveller.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".